| Meta faster r-cnn: Towards accurate few-shot object detection with attentive feature alignment G Han, S Huang, J Ma, Y He, SF Chang Proceedings of the AAAI Conference on Artificial Intelligence 36 (1), 780-789, 2022 | 179 | 2022 |
| Few-shot object detection with fully cross-transformer G Han, J Ma, S Huang, L Chen, SF Chang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 172 | 2022 |
| COVID-19 literature knowledge graph construction and drug repurposing report generation Q Wang, M Li, X Wang, N Parulian, G Han, J Ma, J Tu, Y Lin, H Zhang, ... Proceedings of the 2021 Annual Conference of the North American Chapter of …, 2020 | 163 | 2020 |
| Query adaptive few-shot object detection with heterogeneous graph convolutional networks G Han, Y He, S Huang, J Ma, SF Chang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 136 | 2021 |
| Partner-assisted learning for few-shot image classification J Ma, H Xie, G Han, SF Chang, A Galstyan, W Abd-Almageed Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 88 | 2021 |
| Task-adaptive negative envision for few-shot open-set recognition S Huang, J Ma, G Han, SF Chang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 52 | 2022 |
| Digeo: Discriminative geometry-aware learning for generalized few-shot object detection J Ma, Y Niu, J Xu, S Huang, G Han, SF Chang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 49 | 2023 |
| Supervised masked knowledge distillation for few-shot transformers H Lin, G Han, J Ma, S Huang, X Lin, SF Chang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 43 | 2023 |
| The met dataset: Instance-level recognition for artworks NA Ypsilantis, N Garcia, G Han, S Ibrahimi, N Van Noord, G Tolias NeurIPS 2021 Datasets and Benchmarks Track, 2022 | 42 | 2022 |
| Revisiting Faster R-CNN: a deeper look at region proposal network G Han, X Zhang, C Li International Conference on Neural Information Processing, 14-24, 2017 | 28 | 2017 |
| Multi-modal few-shot object detection with meta-learning-based cross-modal prompting G Han, L Chen, J Ma, S Huang, R Chellappa, SF Chang arXiv preprint arXiv:2204.07841, 2022 | 24 | 2022 |
| Jack of All Tasks Master of Many: Designing General-Purpose Coarse-to-Fine Vision-Language Model S Pramanick, G Han, R Hou, S Nag, SN Lim, N Ballas, Q Wang, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 21 | 2024 |
| Explicit image caption editing Z Wang, L Chen, W Ma, G Han, Y Niu, J Shao, J Xiao European Conference on Computer Vision, 113-129, 2022 | 19 | 2022 |
| Few-shot end-to-end object detection via constantly concentrated encoding across heads J Ma, G Han, S Huang, Y Yang, SF Chang European Conference on Computer Vision, 57-73, 2022 | 17 | 2022 |
| Semi-supervised dff: Decoupling detection and feature flow for video object detectors G Han, X Zhang, C Li Proceedings of the 26th ACM international conference on Multimedia, 1811-1819, 2018 | 15 | 2018 |
| TempCLR: Temporal Alignment Representation with Contrastive Learning Y Yang, J Ma, S Huang, L Chen, X Lin, G Han, SF Chang The Eleventh International Conference on Learning Representations (ICLR), 2023, 2022 | 14 | 2022 |
| Weakly-Supervised Temporal Article Grounding L Chen, Y Niu, B Chen, X Lin, G Han, C Thomas, H Ayyubi, H Ji, ... The 2022 Conference on Empirical Methods in Natural Language Processing …, 2022 | 14 | 2022 |
| Single shot object detection with top-down refinement G Han, X Zhang, C Li 2017 IEEE International Conference on Image Processing (ICIP), 3360-3364, 2017 | 13 | 2017 |
| Mitigating dialogue hallucination for large multi-modal models via adversarial instruction tuning D Park, Z Qian, G Han, SN Lim arXiv preprint arXiv:2403.10492, 2024 | 11 | 2024 |
| Rapidly adaptable automated interpretation of point-of-care COVID-19 diagnostics S Arumugam, J Ma, U Macar, G Han, K McAulay, D Ingram, A Ying, ... Communications Medicine 3 (1), 91, 2023 | 10* | 2023 |
Jiawei Phoenix MAAssistant Professor of Computer Science, City University of Hong Kong在 cityu.edu.hk 的电子邮件经过验证
